Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method of monitoring brain neural activity, the method comprising: repeatedly applying electrical stimuli to evoke evoked compound action potentials in a brain; recording evoked compound action potentials evoked by the stimuli, assessing the recorded evoked compound action potentials for changed characteristics over time, to monitor a time-varying effect of local field potentials on the evoked compound action potentials, the local field potentials arising from a source other than the electrical stimuli.
This invention relates to monitoring brain neural activity by analyzing the effects of local field potentials (LFPs) on evoked compound action potentials (ECAPs). The method involves repeatedly applying electrical stimuli to the brain to evoke ECAPs, which are then recorded. The recorded ECAPs are assessed for changes in their characteristics over time to monitor how LFPs, originating from sources other than the applied stimuli, influence the ECAPs. The technique enables the observation of dynamic interactions between LFPs and neural responses, providing insights into brain function and potential disruptions. The method may be used in neurological research, diagnostic applications, or therapeutic monitoring to track changes in neural activity patterns influenced by endogenous electrical activity. The approach distinguishes between stimulus-evoked responses and spontaneous neural activity, allowing for the isolation and analysis of LFP effects on neural signaling pathways. The system may include electrodes for stimulation and recording, signal processing to extract ECAP features, and analysis algorithms to detect temporal variations in response characteristics. This method supports the study of neural plasticity, disease progression, or the efficacy of interventions targeting brain function.
2. The method of claim 1 , wherein assessing the recorded evoked compound action potentials comprises assessing the amplitude of the recorded evoked compound action potentials.
This invention relates to a method for evaluating neural responses, specifically by analyzing evoked compound action potentials (ECAPs) recorded from neural tissue. The method addresses the challenge of accurately assessing neural activity in response to stimulation, which is critical for applications such as neural prosthetics, neurostimulation devices, and diagnostic tools. The primary focus is on measuring the amplitude of the recorded ECAPs to determine the effectiveness of neural stimulation. The method involves recording ECAPs generated by neural tissue in response to an applied stimulus. By analyzing the amplitude of these signals, the method provides insights into the integrity and functionality of the neural pathways being stimulated. This amplitude assessment helps in evaluating the strength of the neural response, which is essential for optimizing stimulation parameters in medical devices or diagnosing neural disorders. The method may also include additional steps such as filtering the recorded signals to remove noise, comparing the amplitude against predefined thresholds, or adjusting stimulation parameters based on the amplitude measurements. These steps ensure that the recorded ECAPs are accurately interpreted and that the stimulation is effectively tailored to the patient's needs. The amplitude-based assessment is particularly useful in real-time applications where immediate feedback is required to adjust stimulation levels for therapeutic purposes.
3. The method of claim 1 wherein assessing the recorded evoked compound action potentials comprises assessing spectral content of the recorded evoked compound action potentials.
This invention relates to neural signal analysis, specifically assessing evoked compound action potentials (ECAPs) to evaluate neural activity. The method involves recording ECAPs from a neural interface, such as an implanted electrode, and analyzing their spectral content to derive meaningful insights. Spectral analysis helps identify frequency components within the recorded signals, which can indicate the health, responsiveness, or functional state of the neural tissue. By examining the spectral content, the method can detect abnormalities, assess signal quality, or optimize stimulation parameters for therapeutic or diagnostic purposes. This approach is particularly useful in applications like deep brain stimulation, cochlear implants, or peripheral nerve monitoring, where precise neural feedback is critical. The spectral assessment may involve techniques such as Fourier transforms, power spectral density analysis, or frequency-domain filtering to extract relevant features from the ECAP signals. The method improves upon traditional time-domain analysis by providing a more detailed and nuanced understanding of neural responses, enabling better calibration and performance of neural interfaces.
4. The method of claim 3 , further comprising assessing amplitude variations arising in a range of 0.6 to 3 Hz so as to assess a heartbeat.
This invention relates to a method for monitoring physiological signals, specifically focusing on detecting and analyzing heartbeat-related amplitude variations. The method involves assessing amplitude variations within a frequency range of 0.6 to 3 Hz, which corresponds to typical human heartbeat frequencies. By analyzing these variations, the system can determine the presence and characteristics of a heartbeat, enabling applications in medical monitoring, fitness tracking, or other health-related assessments. The method may be part of a broader system that includes signal acquisition, preprocessing, and analysis stages to ensure accurate detection. The frequency range selection is critical, as it filters out irrelevant noise and focuses on the relevant physiological signals associated with cardiac activity. This approach improves the reliability of heartbeat detection in various environments, including wearable devices or clinical settings. The method may also incorporate additional signal processing techniques to enhance accuracy, such as filtering, amplification, or pattern recognition, to distinguish heartbeat signals from other biological or environmental noise. The invention addresses the challenge of accurately detecting heartbeats in real-time, providing a robust solution for continuous monitoring and health assessment.
5. The method of claim 3 , further comprising assessing amplitude variations arising in a beta-band oscillation range of 7-35 Hz.
This invention relates to a method for analyzing neural oscillations, specifically focusing on beta-band oscillations in the frequency range of 7-35 Hz. The method is designed to assess amplitude variations within this frequency range, which is relevant for understanding neural activity patterns in various cognitive and motor functions. The technique involves monitoring neural signals, such as those obtained from electroencephalography (EEG) or other neuroimaging modalities, to detect and quantify fluctuations in beta-band oscillations. These amplitude variations can provide insights into brain function, including motor control, sensory processing, and cognitive states. By analyzing these oscillations, the method aims to identify patterns that may correlate with specific neural processes or disorders, enabling better diagnosis or treatment monitoring. The assessment of beta-band amplitude variations complements broader neural signal analysis techniques, offering a targeted approach to studying brain activity in both healthy and pathological conditions. This method enhances the precision of neural signal interpretation, supporting applications in neuroscience research, clinical diagnostics, and brain-computer interface development.
6. The method of claim 1 wherein the time-varying effect is compared to healthy ranges and/or monitored for changes over time in order to diagnose a disease state.
This invention relates to medical diagnostics, specifically a method for analyzing time-varying physiological effects to detect disease states. The method involves monitoring a patient's physiological data over time to identify deviations from healthy baseline ranges or trends that may indicate disease. The system collects time-series data from sensors or medical devices, processes the data to extract relevant features, and compares these features against predefined healthy ranges. Additionally, the method tracks changes in the data over time to detect progressive or acute conditions. By analyzing these variations, the system can diagnose or predict disease states, such as chronic illnesses or acute conditions, with improved accuracy compared to static measurements. The method may incorporate machine learning or statistical models to enhance detection sensitivity and reduce false positives. This approach enables early intervention by identifying subtle physiological changes that may not be apparent in single-point measurements. The system can be applied to various medical fields, including cardiology, neurology, and endocrinology, to improve diagnostic outcomes.
7. The method of claim 1 wherein the to time-varying effect is compared to healthy ranges and/or monitored for changes over time in order to determine a therapeutic effect of a therapy.
This invention relates to monitoring and evaluating the therapeutic effects of medical treatments by analyzing time-varying physiological effects. The method involves tracking changes in a patient's physiological response over time to assess the effectiveness of a therapy. The system compares these time-varying effects against predefined healthy ranges to determine whether the therapy is producing the desired therapeutic outcome. Additionally, the method monitors for deviations or trends in the physiological data to detect changes that may indicate the therapy's efficacy or potential adverse effects. The analysis may include continuous or periodic measurements of physiological parameters, such as heart rate, blood pressure, or other relevant biomarkers, to provide real-time or delayed feedback on treatment progress. By comparing the observed effects to established healthy ranges, the system can objectively evaluate whether the therapy is achieving its intended benefits. The method may also incorporate machine learning or statistical models to predict future therapeutic outcomes based on historical data trends. This approach enables clinicians to make data-driven adjustments to treatment plans, optimizing patient care and improving therapeutic decision-making.
8. The method of claim 1 , further comprising indicating a therapeutic response, based on the time-varying effect.
This invention relates to a method for monitoring and analyzing time-varying effects in a biological system, particularly for assessing therapeutic responses. The method involves measuring a biological signal, such as electrical activity, over time to detect changes in the signal's characteristics. These changes are analyzed to determine a time-varying effect, which reflects how the biological system responds to an intervention, such as a drug or treatment. The method further includes indicating a therapeutic response based on the observed time-varying effect, allowing for real-time or delayed assessment of treatment efficacy. The biological signal may be obtained from various sources, including neural, cardiac, or muscular tissues, and the analysis may involve statistical or machine learning techniques to identify patterns or deviations in the signal. The method can be applied in clinical settings to optimize treatment protocols or in research to study biological responses to stimuli. By quantifying the time-varying effect, the invention provides a more precise and dynamic way to evaluate therapeutic outcomes compared to traditional static measurements.
9. A brain neurostimulator device comprising: at least one stimulus electrode configured to be positioned in a brain and to deliver electrical stimuli to the brain; at least one sense electrode configured to be positioned in the brain and to sense evoked compound action potentials evoked by the stimuli; a pulse generator configured to apply electrical stimuli from the at least one stimulus electrode to the brain; measurement circuitry configured to record brain evoked compound action potentials sensed by the at least one sense electrode in response to the electrical stimuli; and a processor for assessing the recorded evoked compound action potentials for changed characteristics over time, to monitor a time-varying effect of local field potentials on the evoked compound action potentials, the local field potentials arising from a source other than the electrical stimuli.
This invention relates to a brain neurostimulator device designed to deliver electrical stimuli to the brain while monitoring neural responses. The device includes at least one stimulus electrode positioned in the brain to deliver electrical pulses and at least one sense electrode to detect evoked compound action potentials (ECAPs) generated by these stimuli. A pulse generator controls the delivery of electrical stimuli, while measurement circuitry records the ECAPs sensed by the electrodes. A processor analyzes the recorded ECAPs to detect changes in their characteristics over time, allowing for the assessment of neural activity modulation. Additionally, the processor monitors how local field potentials (LFPs)—arising from sources other than the applied stimuli—affect the ECAPs, providing insights into dynamic neural interactions. This system enables real-time or delayed evaluation of neural responses to stimulation, facilitating adaptive neurostimulation therapies for conditions like epilepsy, Parkinson’s disease, or other neurological disorders. The device integrates stimulation and sensing functions to optimize therapeutic outcomes by continuously assessing neural activity and adjusting stimulation parameters accordingly.
10. A computer program product comprising computer program code means for monitoring brain neural activity, the computer program code means configured to: repeatedly apply electrical stimuli to evoke evoked compound action potentials in the brain; record evoked compound action potentials evoked by the stimuli; and assess the recorded evoked compound action potentials for changed characteristics over time, to monitor a time-varying effect of local field potentials on the evoked compound action potentials, the of local field potentials arising from a source other than the electrical stimuli.
This invention relates to a system for monitoring brain neural activity by analyzing evoked compound action potentials (ECAPs) in response to electrical stimulation. The system applies repeated electrical stimuli to evoke ECAPs in the brain, records these responses, and assesses changes in their characteristics over time. The assessment focuses on detecting how local field potentials (LFPs), originating from sources other than the applied stimuli, influence the ECAPs. This approach enables tracking dynamic interactions between neural activity patterns and external or internal neural signals, providing insights into neural function and potential disruptions. The system may be used in applications such as neurological research, diagnostic monitoring, or therapeutic interventions where understanding neural plasticity or pathological changes is critical. The recorded ECAPs are analyzed to identify variations in amplitude, timing, or waveform morphology, which reflect the modulatory effects of LFPs on neural signal propagation. By isolating these effects, the system distinguishes between direct stimulation responses and indirect influences from ongoing neural activity, improving the accuracy of neural monitoring. The invention may be implemented in implantable or external devices for continuous or periodic assessment of brain function.
11. The brain neurostimulator device of claim 9 , wherein the processor is further configured to assess the recorded evoked compound action potentials by assessing the amplitude of the recorded evoked compound action potentials.
The brain neurostimulator device is designed to monitor and stimulate neural activity in the brain, particularly for therapeutic purposes such as treating neurological disorders. The device includes a processor that records evoked compound action potentials (ECAPs) generated in response to neural stimulation. These ECAPs are electrical signals that reflect the collective activity of a group of neurons. The processor is configured to analyze these recorded ECAPs by evaluating their amplitude, which provides insights into the effectiveness of the stimulation and the state of neural activity. By assessing the amplitude of the ECAPs, the device can determine whether the stimulation is producing the desired neural response, allowing for real-time adjustments to optimize therapy. This amplitude-based assessment helps ensure that the stimulation parameters are appropriate for the patient's condition, improving treatment efficacy and reducing the risk of adverse effects. The device may also include additional features, such as adaptive stimulation algorithms, to dynamically adjust stimulation parameters based on the recorded neural signals. This closed-loop approach enhances the precision and personalization of neural modulation therapies.
12. The brain neurostimulator device of claim 9 wherein the processor is further configured to assess the recorded evoked compound action potentials by assessing spectral content of the recorded evoked compound action potentials.
The brain neurostimulator device is designed to deliver electrical stimulation to neural tissue and monitor the resulting neural activity. The device includes a stimulation module that generates electrical pulses to target specific brain regions, and a recording module that captures evoked compound action potentials (ECAPs) from the stimulated neural tissue. These ECAPs are electrical signals generated by the collective activity of neurons in response to stimulation. The device further includes a processor that analyzes the recorded ECAPs by evaluating their spectral content. Spectral analysis involves decomposing the ECAP signals into their frequency components to assess the neural response characteristics. This analysis helps determine the effectiveness of the stimulation, identify changes in neural activity, and optimize stimulation parameters for therapeutic purposes. The processor may use techniques such as Fourier transforms or wavelet analysis to extract relevant frequency information from the ECAP signals. By assessing the spectral content of the ECAPs, the device can provide insights into neural function and adapt stimulation protocols in real-time to improve treatment outcomes. This approach is particularly useful in applications such as deep brain stimulation, where precise control of neural activity is critical for managing conditions like Parkinson’s disease, epilepsy, or chronic pain. The spectral analysis of ECAPs allows for more accurate and personalized neurostimulation therapies.
13. The brain neurostimulator device of claim 12 wherein the processor is further configured to assess amplitude variations arising in a range of 0.6 to 3 Hz so as to assess a heartbeat.
This invention relates to a brain neurostimulator device designed to monitor and analyze neural activity, particularly focusing on detecting heartbeat-related signals in the brain. The device includes a processor configured to assess amplitude variations in neural signals within a specific frequency range of 0.6 to 3 Hz, which corresponds to heartbeat-related oscillations. By analyzing these variations, the device can derive information about the heartbeat, potentially aiding in the diagnosis or monitoring of neurological conditions influenced by cardiovascular activity. The processor may also be configured to perform additional signal processing tasks, such as filtering or amplifying neural signals, to enhance the accuracy of heartbeat detection. The device is intended for use in clinical or research settings where precise monitoring of brain activity and its correlation with physiological processes like heartbeat is required. The invention addresses the challenge of non-invasively detecting and interpreting heartbeat-related neural signals, which can be obscured by other brain activity or noise. By focusing on the 0.6 to 3 Hz range, the device improves the specificity and reliability of heartbeat assessment in neural recordings.
14. The brain neurostimulator device of claim 12 , wherein the processor is further configured to assess amplitude variations arising in a beta-band oscillation range of 7-35 Hz.
The invention relates to a brain neurostimulator device designed to monitor and modulate neural activity, particularly focusing on beta-band oscillations in the frequency range of 7-35 Hz. This device addresses the challenge of detecting and analyzing specific neural oscillations associated with conditions like Parkinson's disease, essential tremor, or other movement disorders, where abnormal beta-band activity is often observed. The neurostimulator includes a processor that evaluates amplitude variations within this frequency range, enabling precise identification of neural patterns that may indicate pathological states or treatment efficacy. By continuously assessing these oscillations, the device can provide real-time feedback for adaptive stimulation strategies, improving therapeutic outcomes. The processor's ability to analyze beta-band activity allows for targeted interventions, such as deep brain stimulation (DBS), to be adjusted dynamically based on neural signal characteristics. This enhances the device's effectiveness in managing symptoms by ensuring stimulation parameters align with the patient's current neural state. The invention thus offers a sophisticated approach to neurostimulation, leveraging frequency-specific analysis to optimize treatment for neurological disorders.
15. The brain neurostimulator device of claim 9 wherein the processor is further configured to compare the time-varying effect to healthy ranges, and/or monitor the time-varying effect for changes over time, in order to diagnose a disease state.
A brain neurostimulator device is designed to monitor and modulate neural activity for therapeutic purposes. The device includes a processor that analyzes the time-varying effects of neural stimulation on brain activity. This analysis involves comparing the observed effects to predefined healthy ranges to detect deviations that may indicate a disease state. Additionally, the processor can track changes in these effects over time to identify progressive conditions or treatment efficacy. The device may also adjust stimulation parameters based on the monitored effects to optimize therapeutic outcomes. By continuously assessing neural responses, the system aids in diagnosing neurological disorders and personalizing treatment strategies. The technology addresses the challenge of accurately diagnosing and managing brain-related conditions by providing real-time, data-driven insights into neural function.
16. The brain neurostimulator device of claim 9 wherein the processor is further configured to compare the time-varying effect to healthy ranges, and/or monitor the time-varying effect for changes over time, in order to determine a therapeutic effect of a therapy.
This invention relates to a brain neurostimulator device designed to deliver electrical stimulation to the brain for therapeutic purposes. The device includes a processor that analyzes the time-varying effects of the stimulation on neural activity. The processor compares these effects to predefined healthy ranges to assess whether the stimulation is achieving the desired therapeutic outcome. Additionally, the processor monitors changes in the time-varying effects over time to track the progression of the therapy's effectiveness. This allows for real-time adjustments to the stimulation parameters to optimize treatment. The device may also include electrodes for delivering the stimulation and sensors for measuring neural activity, ensuring precise and adaptive therapy delivery. The system is particularly useful for conditions where brain activity needs to be modulated, such as epilepsy, Parkinson's disease, or depression, by providing a closed-loop approach that continuously evaluates and adjusts the stimulation based on neural responses. The invention improves upon existing neurostimulation devices by incorporating dynamic monitoring and comparison to healthy baselines, enhancing therapeutic precision and efficacy.
17. The brain neurostimulator device of claim 9 wherein the processor is further configured to indicate a therapeutic response, based on the time-varying effect.
A brain neurostimulator device is designed to deliver targeted electrical stimulation to the brain to treat neurological disorders such as epilepsy, Parkinson's disease, or chronic pain. The device includes a processor that analyzes the brain's electrical activity and adjusts stimulation parameters in real-time to optimize therapeutic effects. A key feature is the processor's ability to detect and measure time-varying effects of the stimulation on brain activity, allowing it to dynamically adapt stimulation patterns to maintain efficacy. The processor also evaluates these time-varying effects to determine whether the stimulation is producing a therapeutic response, such as reduced seizure activity or improved motor function. This feedback mechanism ensures that the device continuously adjusts to the patient's changing neurological state, enhancing treatment precision and effectiveness. The system may include electrodes implanted in the brain, external or implantable pulse generators, and sensors to monitor brain signals. The adaptive stimulation approach aims to minimize side effects and improve long-term outcomes by tailoring therapy to individual patient needs.
Unknown
December 1, 2020
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